Instead of focusing on replacing humans, JobBench evaluates AI across 130 real-world tasks that experts want to delegate. The new Claude Opus 4.7 only scored 45.9%.
IBM Research argues that while LLMs are powerful, scalable enterprise adoption requires "Agent Logic"—software primitives like knowledge graphs and program analysis—to steer agents reliably and cost-effectively within complex workflows.
The Agency offers a collection of specialized AI agents, from frontend development to community management, each with its own personality and workflow, ready to optimize your workflow.
Clement Delangue (Hugging Face) has warned that many Reinforcement Learning (RL) training pipelines for Agentic LLMs are currently buggy without developers realizing it. While single-turn RL operates stably, adding tools for mid-rollout interaction often causes the system to lose control or converge in the wrong direction.
MiniMax has launched the M2 MoE model series with 229.9 billion parameters, optimized for agents and capable of self-debugging its own source code.
